AI & LLM Engineering · Hugging Face

Logs and visualizes ML training metrics with Trackio, firing alerts for issues like loss spikes, and syncing a live dashboard to a Hugging Face Space.

huggingface/skills

Fetch and summarize recent AI news from curated RSS feeds (Hugging Face, VentureBeat, The Verge, OpenAI, Anthropic, DeepMind, etc.) and YouTube channels (Yannic Kilcher, Two Minute Papers, AI…

letta-ai/skills

A skill your agent uses when the user asks to "scout for new models", "check for model updates", "find better ASR models", "check sherpa-onnx releases", "look for new Whisper models", "search…

RisorseArtificiali/anti-vocale

Review and repair pull requests on the evaleval/EEEdatastore Hugging Face dataset.

evaleval/every_eval_ever

Benchmarks code generation models with the BigCode Evaluation Harness across HumanEval, MBPP, MultiPL-E and other suites using pass@k metrics.

Orchestra-Research/AI-Research-SKILLs

Integrate a new text-to-speech model into vLLM-Omni from HuggingFace reference implementation through production-ready serving with streaming and CUDA graph acceleration.

vllm-project/vllm-omni

HuggingFace Transformers integration for PerforatedAI. An agent skill from PerforatedAI/PerforatedAI.

PerforatedAI/PerforatedAI

Produces ranked, evidence-grounded next steps when an ML experiment has stalled, drawing on a Leeroopedia knowledge base or on fetched docs and issues.

Leeroo-AI/superml

Adds distributed and mixed-precision training to a PyTorch script with a few Accelerate lines, then launches it on one GPU, many GPUs or DeepSpeed and FSDP setups.

Orchestra-Research/AI-Research-SKILLs

Explores Hugging Face datasets through the read-only Dataset Viewer API: list splits, preview and page through rows, search, filter, and fetch parquet links and statistics.

huggingface/skills

Fetches Hugging Face paper pages as markdown and reads paper metadata through the papers API when you share a paper URL, an arXiv link or an arXiv ID.

huggingface/skills

Finds models on the Hugging Face router that lack descriptions in chat-ui's prod.yaml and dev.yaml, researches each one and adds short descriptions.

ruvnet/ruflo

Uses Ray Data to read, transform and write large datasets across a cluster for ML training and batch inference, with streaming execution and optional GPU steps.

Orchestra-Research/AI-Research-SKILLs

Covers the rules for writing Gradio Spaces on ZeroGPU hardware: the @spaces.GPU decorator, duration and quota tuning, process isolation and CUDA build limits.

huggingface/skills

Best practices for multi-step Python tasks including data analysis, HuggingFace datasets, token counting, and any task requiring state across multiple python() calls.

A-EVO-Lab/a-evolve

Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub

huggingface/skills

Checks training code, configs and math against documented framework behavior before an expensive run, citing a knowledge base or official docs for every claim.

Leeroo-AI/superml

Register, list, get, and manage LLM models in OCI AI Quick Actions (AQUA) using the ADS SDK.

oracle/accelerated-data-science

Guide users through Cosmos3 supervised fine-tuning (SFT) post-training: preparing the example dataset and Wan2.2 VAE, converting the base checkpoint to DCP, launching distributed training (paired…

NVIDIA/cosmos-framework

Finds top models for a task from official Hugging Face benchmark leaderboards, filters them to what fits your hardware, and returns a comparison table with scores.

huggingface/skills

Builds and publishes a Gradio demo on Hugging Face Spaces for a LoRA, with the pipeline, UI and settings chosen to match that LoRA's task and model card.

huggingface/skills

A skill your agent uses when adding, debugging, or validating a bring-your-own VLM in VSS RT-VLM, including custom Hugging Face or NGC checkpoints, vLLM adapters or plugins, model shims, and…

NVIDIA-AI-Blueprints/video-search-and-summarization

Convert a HuggingFace ASR fine-tune into a sherpa-onnx external model, publish it, and add it to the Anti-Vocale community catalog.

RisorseArtificiali/anti-vocale

Estimate GPU memory usage for Megatron-based MoE (Mixture of Experts) and dense models.

yzlnew/infra-skills

Half-Quadratic Quantization for LLMs without calibration data.

Orchestra-Research/AI-Research-SKILLs

Train Mixture of Experts (MoE) models using DeepSpeed or HuggingFace.

Orchestra-Research/AI-Research-SKILLs

Guides causal experiments on PyTorch models with pyvene, such as causal tracing, activation patching and interchange intervention training, to test how a model works.

Orchestra-Research/AI-Research-SKILLs

Loads large language models in 8-bit or 4-bit with bitsandbytes so they fit smaller GPUs, and sets up QLoRA fine-tuning on a 4-bit base model.

Orchestra-Research/AI-Research-SKILLs

Scales PyTorch, TensorFlow and Hugging Face training from a single GPU to multi-node clusters with Ray Train, including Ray Tune sweeps and checkpoint recovery.

Orchestra-Research/AI-Research-SKILLs

Generates text embeddings locally with the sentence-transformers library for RAG, semantic search, clustering and similarity, with model picks for general, multilingual and legal text.

Orchestra-Research/AI-Research-SKILLs

Explains three ways to speed up LLM inference: draft-model speculative decoding, Medusa heads and lookahead decoding with Jacobi iteration, and when each one fits.

Orchestra-Research/AI-Research-SKILLs

Guides reinforcement-learning research with torchforge, Meta's PyTorch-native library that keeps RL algorithms apart from infrastructure, including GRPO math-reasoning runs.

Orchestra-Research/AI-Research-SKILLs

Trains LLMs with reinforcement learning using verl, from ByteDance's Seed team, with GRPO, PPO and other algorithms and swappable training and rollout backends.

Orchestra-Research/AI-Research-SKILLs

Guide developers through creating a custom data ingestor plugin for AutoRAG-Research.

NomaDamas/AutoRAG-Research

Loads pre-trained Hugging Face Transformers models for text, vision and audio tasks, runs inference with pipelines and fine-tunes on custom datasets.

davila7/claude-code-templates

Build, deploy, and maintain applications on Hugging Face Spaces — Gradio / Docker / Static SDKs, ZeroGPU and dedicated hardware, model loading, debugging, buckets, inference providers, community…

huggingface/skills

Deploy vLLM to Kubernetes (K8s) with GPU support, health probes, and OpenAI-compatible API endpoint.

vllm-project/vllm-skills

Search all Japanese NLP resources (libraries, models, datasets, tutorials, dictionaries, Hugging Face).

taishi-i/awesome-japanese-nlp-resources

Explains how to train a model to be harmless with self-critique, revision and AI-generated preference feedback, with Hugging Face and TRL code for each stage.

Orchestra-Research/AI-Research-SKILLs

Fills and maintains the knowledgeCutoff, family and generation fields on model cards in LobeHub's model bank, from a single new model up to repo-wide backfills.

lobehub/lobehub

A skill your agent uses when converting Hugging Face SafeTensors checkpoints into split BF16 GGUF model repos with skippy-quantize on Hugging Face Jobs or a local machine, then publishing the…

Mesh-LLM/mesh-llm

Guides GRPO reinforcement-learning fine-tuning of language models with TRL, centered on designing reward functions for formats, verifiable tasks and reasoning.

Orchestra-Research/AI-Research-SKILLs

Run the Nemotron-3.5 Lightning Text2SQL LoRA fine-tuning tutorial (NeMo Megatron-Bridge) end-to-end for the user on a single node: data prep, checkpoint conversion, LoRA fine-tuning of the 30B-A3B…

NVIDIA-NeMo/Nemotron

Use Hugging Face Hub via MCP server tools. An agent skill from huggingface/skills.

huggingface/skills

Guide to using Mamba selective state-space models for linear-time sequence modeling, from the Mamba block and pretrained checkpoints to Mamba-2 and speed comparisons.

Orchestra-Research/AI-Research-SKILLs

Orchestrates video data augmentation and auto-labeling workflows on OSMO, from flow selection and preflight checks to submission, monitoring and output download.

NVIDIA/skills

Entry point for hosting a model on Amazon SageMaker: asks a few questions, picks a deployment pathway and hands off to the specialist skills.

huggingface/skills

Reference for post-training language models with TRL: which trainer and dataset format to use for SFT, DPO, GRPO, KTO and reward models, and how to add LoRA.

huggingface/skills